Services portal

ABSTRACT

An apparatus for monitoring performance of an industrial process includes a service portal for collecting, transmitting and analyzing parameter data from process field devices that includes a network connection that connects to a process control system of the industrial process, a remote collector that collects parameter data from process field devices, a processor that identifies, sorts, and stores the collected parameter data and a communications module for transmitting the stored parameter data to a remote monitoring station for analysis.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a divisional of U.S. patent application Ser. No.12/016,576, filed Jan. 18, 2008, titled SERVICES PORTAL, which is acontinuation of U.S. patent application Ser. No. 10/680,411, filed Oct.8, 2003, titled SERVICES PORTAL, now U.S. Pat. No. 7,328,078, whichclaims priority to U.S. Provisional Application Ser. No. 60/416,538,filed Oct. 8, 2002, titled PERFORMANCE STATION, all of which are herebyincorporated by reference in their entirety.

TECHNICAL FIELD

This disclosure relates to industrial processes, and more particularlyto optimization of industrial systems.

BACKGROUND

A great challenge of managing industrial systems and process plants isthe ability to improve and validate system performance. Companies wantstable system platforms that all but eliminate downtime.

Many factors affect system stability and downtime. For example, thesefactors range from human aspects such as inadequate, incorrect orconfusing procedures, and insufficient training to other factors such aspoor system/application design and engineering and improper or less thanoptimum equipment. Various mechanisms have been developed to account forand/or monitor some of these factors. However, there exists a demand fornew methods and technology to supplement traditional mechanisms used toprovide system stability and improve performance.

SUMMARY

In one general aspect, a proactive monitoring and reporting appliancecollects information from various field devices that are part of anindustrial process to enable proactive, predictive remote monitoringservices that implement a dynamic performance strategy. Unlike faulttolerant systems, that allow for system failures and continue to operatedespite them, proactive, predictive remote monitoring seeks to avoidfailures altogether. Therefore, a predictive analysis monitor isprovided to identify potential and intermittent hardware, network,application faults and potential system unreliability issues beforefailures occur. Once identified, the predictive analysis monitor givesadvance warning through alarm messaging either back to a remoteperformance-monitoring center and/or to a local interface.

The predictive analysis monitor obtains data from various event logfiles or on site process controllers or gathers process parameter datadirectly from the field devices. The predictive analysis monitor thenapplies data pattern/signatures, thresholds, tolerances and analysistechniques to detect and classify faults or instabilities and todiagnose potential failures. Each of these thresholds, tolerances andanalysis techniques undergo expert review and analysis to assist in thediagnosis and to verify and validate any proposed solutions.

The predictive analysis monitor also gathers data to assist inoptimizing the current process and to achieve improved economic valuefrom the process, a greater return on investment for capital equipmentand from the process.

The predictive analysis monitor can be used as part of a businessrelationship established between the supplier and amanufacturing/processing company whereby the services portal and theanalysis provided from its data collection and analysis, including theexpert analysis provided by the supplier's experts, are provided by thesupplier as a service to the manufacturing company, who may lease theservices portal.

In one general aspect, a method of improving a manufacturing client'sbusiness performance includes determining a current baseline businessperformance for the client including identifying targeted areas ofimprovement in the manufacturing area, analyzing potential economic gainthat may be realized for each targeted area, identifying dynamicperformance measures for each targeted area, monitoring industrialprocess parameters within the target areas and developing baselinedynamic performance measures of the target areas, analyzing the baselinedynamic performance measures to identify areas for optimization withinthe industrial process, and optimizing the industrial process parametersbased on the analysis of the baseline measures. Determining a currentbaseline business performance for the client can include on site studyof the plant process.

In one aspect, identifying targeted areas of improvement may includeidentification of deficient performance of the process using economicanalyses. Identifying dynamic performance measures for each targetedarea may include identifying measurable process parameters that aredirectly related to economic performance of the targeted area.

Monitoring industrial process parameters within the target areas anddeveloping baseline dynamic performance measures of the target areas caninclude observing multiple performances of the processes associatedwithin each target area, and evaluating economic effects of theindividual industrial process parameters. Monitoring industrial processparameters can also include establishing a baseline optimum value foreach process parameter based on multiple performances of each process.

Analyzing the baseline dynamic performance measures to identify areasfor optimization within the industrial process may include evaluatingthe economic effects on the product of the industrial processparameters.

In another general aspect a method of optimizing industrial productionincludes providing an onsite production process parameter-monitoringdevice to a client for monitoring the parameters of a set of fielddevices associated with a client production process where the monitoringdevice can transmit process data offsite for analysis. This method caninclude associating the monitoring device with a data output of eachfield device within the set of field devices, where each field devicegathers process parameter data associated with an operation performedand transmits the data to the monitoring device associated with theprocess. Each field device can be monitored through a plurality ofperformances of the process, while gathering parameter data from eachperformance and transmitting the gathered data offsite for analysis.Gathering parameter data for each performance of a field device caninclude splitting the data stream from each field device into individualprocess parameter data, creating a data historian for each parameter,for each field device and for each production process, storing the datain an on-site central data collection device and in an offsite storageand analysis device.

In one aspect the method can also include maintaining an on site centraldata collection device wherein all of the data associated with theprocess is collected for on site and offsite use. Associating themonitoring devices with a data output of every individual field devicecan include defining a potential data output stream from each fielddevice and establishing a data communications link between each fielddevice and the associated monitoring device. In this aspect, defining apotential data output stream can include identifying relevant processparameters, and ensuring that each relevant process parameter is beingmonitored. Establishing a data communications link between each fielddevice and the associated monitoring device includes linking the fielddevices to the associated monitoring device using any combination ofwireless, infrared, RF, direct connect, POTS, Ethernet, LAN, WAN,internet, intranet, fiber optic, optical, or any other type ofcommunications link that can be made between two or more data storage orprocessing devices. Similarly, the monitoring devices transmit the dataoffsite using any combination of wireless, infrared, RF, direct connect,POTS, Ethernet, LAN, WAN, internet, intranet, fiber optic, optical, orany other type of communications link that can be made between two ormore data storage or processing devices.

A method of optimizing industrial production includes providing aplurality of onsite production process parameter monitoring devices to aclient for monitoring the parameters of a set of field devicesassociated with each client product wherein each monitoring device cantransmit process data to an offsite analysis group, associating themonitoring devices with a data output of each field device in the set offield devices, wherein each field device gathers process parameter dataassociated with the operation performed and transmits the data to themonitoring device associated with the process, monitoring each fielddevice through a plurality of performances of the process, whilegathering parameter data from each performance, transmitting thegathered data offsite for analysis, and analyzing the gathered dataoffsite using process experts, wherein the process experts developoptimal physical parameter ranges for each field device of each clientproduction process.

In one aspect, the method of optimizing industrial production can alsoinclude an on-site central data collection device wherein all of thedata transmitted offsite is collected for on-site use. This method canalso include transmitting the optimal physical parameters for each fielddevice of each client production process to the client and makingadjustments to a field device controller for each field device, whereinthe adjustments are based on the analysis of the data performed by theexperts. The data analysis can include developing a statistical modelfor the data, developing simulation models of the process using thedata, and doing a trend analysis of the data. The adjustments can bemade in the process while the process is running or while the process isidle and can result in optimal productivity for the process.

An apparatus for monitoring performance of an industrial process caninclude a service portal for collecting, transmitting and analyzingparameter data from process field devices. The service portal caninclude a network connection that connects to a process control systemof the industrial process, a remote collector that collects parameterdata from process field devices, a processor that identifies, sorts, andstores the collected parameter data, and a communications module fortransmitting the stored parameter data to a remote monitoring stationfor analysis. The network connection can be a wireless networkconnection, an optical network connection, a radio frequency networkconnection, a LAN, a WAN, a POTS, a SONNET network, a DSL connection, anISDN connection or any other type of network connection. The remotecollector can collect the parameter data from a workstation. Theprocessor may perform simple analysis of the parameter data includingtrends analysis, statistical analysis, data modelling and simulationdevelopment of the process.

The details of one or more implementations of the invention are setforth in the accompanying drawings and the description below. Otherfeatures will be apparent from the description and drawings, and fromthe claims.

DESCRIPTION OF DRAWINGS

FIG. 1 is a block diagram of a performance station.

FIG. 2 is a diagram of a services portal connected to an exemplaryindustrial processing system.

FIG. 3 is a diagram of an application probe object showing some of thepossible inputs.

FIG. 4 is a flowchart of an example of the performance allianceagreement business model.

Like reference symbols in the various drawings indicate like elements.

DETAILED DESCRIPTION

Overview

Many industrial processes are implemented by various resources ordevices located throughout an industrial system. Continuous, batch andsemi-batch industrial processes are implemented by various field devicesthat are automated and may be controlled by intelligent automatedsystems. Intelligent automated systems include various process controlsystems including programmable logic controllers (PLC), processors,workstations, communications systems software and related infrastructurethat monitor and control the field/plant devices to implement theindustrial processes.

Intelligent automated systems provide information to business systemsthat manage the industrial processes. For example, the business systemsmay be used to supervise and control the intelligent automated systemsand ensure that the processes are operating as desired. The businesssystems also may be used to implement business decisions, adjustproduction and process parameters, and generally control the industrialprocesses.

To improve overall system performance, proactive, predictive monitoringservices and reporting stations collect information from the intelligentautomated systems to implement a dynamic performance strategy. Unlikefault tolerant systems that allow for system failures, proactive,predictive remote monitoring services help to avoid failures altogetherand improve system availability and performance.

Proactive, predictive monitoring services improve system performance byidentifying potential and intermittent field device, hardware, network,and application faults, and potential system unreliability orinstability issues throughout the monitored industrial process. Onceidentified, various indications and advance warnings are provided byanalysis reports, alarm messaging, and graphical user interfaces. Theindication and advanced warnings may be provided to or identified by aremote performance-monitoring center and/or on site to a local operatorso that appropriate action may be taken to maintain or optimize systemavailability and performance.

A services portal provides a platform for the proactive, predictivemonitoring services. A predictive analysis monitor obtains data fromvarious event log files from workstations or on site processcontrollers. The predictive analysis monitor stores and reports thecollected data, and provides data threshold alarming, rate-of-changealarming, and trend alarming, based on the collected data.

The predictive analysis monitor also provides analysis tools, such as,predictive failure analysis, loop performance analysis, assetmanagement, process modeling, and performance modeling. The predictiveanalysis monitor applies the analysis tools to the log files andcollected data to help detect and classify faults, to diagnose potentialfailures, and to improve/maintain system performance. As a result,system performance is increased by proactively monitoring criticalindustrial control processes to maximize system availability, uptime,and use of system resources. The predictive analysis monitor alsoreduces maintenance time and cost through predictive maintenance usingthe analysis tools to provide notification of the deterioration ofsystem component health and through comprehensive graphical userinterfaces, and reporting.

System Overview

FIG. 1 shows one implementation of a services portal 105 withperformance analysis monitor 100 that can be connected to a variety ofautomated industrial process systems. The services portal 105 is thehardware portion of the system while the performance analysis monitor100 performs the software and data analysis functions. The servicesportal includes a remote collector 110, which connects to the variouslevels of the industrial process. The remote collector 110 can connectand/or communicate directly with application objects (described ingreater detail below) at the individual field devices or workstations,collecting data representing the process parameters at the point ofmeasurement, or can connect and/or communicate with an industrialprocess' integrated controller or host workstation and can collect dataat that level. In addition, the remote collector 110 can connect to,communicate with, and collect and interpret data from applicationobjects at all other levels of controllers and process parameterindicators, analog or digital, including independent workstations,programmable logic circuits, proportional, proportional-integral,proportional-integral-derivative controllers, host workstations,automated process controllers, distributed control systems, centralizedcontrol systems, individual sensors, handheld data collection devices,servers, mini computers, and any other devices used to indicate processdata values or control processes.

The information can come in various forms such as real-time individualvalues to stored historic data and can be recognized, sorted and storedin the performance analysis monitor's historian database. The individualconnections can be wireless, infrared, optical, RF, Ethernet, LAN, WAN,POTS, SONNET, and other common data communications types or combinationsof data communication types. As the data from the industrial process isgathered by the remote collector 110, the performance analysis monitor100 can send the data to a processor 120 that includes a loop analystprocess 125 to perform an initial real time data analysis of the processincluding a loop analysis. While monitoring the process, the performanceanalysis monitor 100 can build an historian database 130 that recordsthe historical parameters of the industrial process. This historian 130can be accessed either locally or remotely to conduct optimizationanalysis on the industrial process from the top level all the way downto the individual field device level. The services portal 105 includes atelecommunications module 140 that may communicate through a network 150in order to remotely report alarm status, provide for remote access, andto provide maintenance access and reporting to a remote monitoringservice 160. The network 150 may be a LAN, WAN or other communicationsnetwork including the Internet. All communications external to theprocess network can be security protected using a variety of protectionschemes including firewalls and data encryption.

Performance Analysis System

FIG. 2 shows the performance analysis monitor 100 connected to aclient's industrial process. The performance analysis monitor 100 mayinclude connections to various field devices 210 that implement one ormore industrial field processes. Other connections may be to one or moreprocess control devices 220 that implement intelligent automatedapplications to control the field devices 210 and the system processes.

The process control devices 220 can communicate on various network datapaths 230. The process control devices 220 can be individualworkstations 250, integrated process controllers 221 that are part ofthe field device 210, hand held process controllers that supplyindividual instructions to and retrieve real time and archived data fromfield devices throughout the process (not shown), and host workstations290 that gather data from a variety of process field devices andworkstations 250. The communications network data path 230 may beimplemented using various communication media and networks. Thecommunications network path 230 may be configured to send and receivesignals (e.g., electrical, electromagnetic, RF, or optical) that conveyor carry data streams representing various types of analog and/ordigital content. For example, the communications network path 230 may beimplemented using various communications media and one or more networkscomprising one or more network devices. Examples of these may beservers, routers, switches, hubs, repeaters, and storage devices. Theone or more networks may include a WAN, a LAN, an Ethernet, a plain oldtelephone service (POTS) network, a digital subscriber line (DSL)network, an integrated services digital network (ISDN), a synchronousoptical network (SONNET), a wireless network or a combination of two ormore of these networks. In addition, the communications network path 230may include one or more wireless links that transmit and receiveelectromagnetic signals, such as, for example, radio, infrared,electromagnetic and microwave signals, to convey information. In oneimplementation, the process control devices 220 are connected usingEthernet connections.

The services portal 105 is connected to the control devices through asystem network 240. The network may include any number of componentsand/or network devices such as hubs, routers, switches, servers,repeaters, storage devices, communications interfaces, processors, andvarious communications media to establish a local area network (LAN), awide area network (WAN), a switched network, a radio network, a cablenetwork, or a satellite network, or a combination of two more of thesenetworks. In one implementation, the services portal 105 may beconnected to various controllers by a TCP/IP Ethernet LAN.

As shown in FIG. 2, a performance analysis system 200 may include one ormore workstations 250 that monitor and control various field devices210. Each of the workstations 250 may include a general orspecial-purpose computer capable of responding to, generating, andexecuting instructions in a defined manner. The workstations 250 mayinclude any number of other devices, components, and/or peripherals,such as memory/storage devices, input devices, output devices, userinterfaces, and/or communications interfaces.

The workstations 250 also may include one or more software applicationsloaded on workstations 250 to command and direct each workstation 250.Applications may include a computer program, a piece of code, aninstruction, or some combination thereof, for independently orcollectively instructing the workstation 250 to interact and operate asdesired.

The applications may be embodied permanently or temporarily in any typeof machine, component, physical or virtual equipment, storage medium, orpropagated signal wave capable of providing instructions to theworkstation 250. In particular, the applications may be stored on astorage medium or device (e.g., a read only memory (ROM), a randomaccess memory (RAM), a volatile/non-volatile memory, or a magnetic diskreadable by the workstation, such that if the storage medium or deviceis read by the workstation, the specified steps or instructions areperformed.

Each workstation 250 may include one or more block processors 260 thatreceive process data associated with system resources (e.g., freememory, disk space, control processor loading, configurable operatingsystem resources, and kernel resources). The block processors 260identify user-defined and enabled block types from the block database295 and sets up application objects 215 to collect and store datagathered by data probes 270 associated with a specific field device 210.

Each workstation 250 may also include one or more data probes 270 thatare associated with various processes and system resources. The dataprobes 270 supply resource and process data used by the predictiveperformance monitoring services. The data probes 270 may be implementedusing software that monitor, collect, and populate application objects215 with field device parameter data. The data probes 270 extractreal-time and archived data (where available) from the individual fielddevices 210. The application objects 215 gather the extracted fielddevice data, resource data and process information supplied by the dataprobes 270. In one implementation, there is a one-to-one relationshipbetween an application object 215 and a data probe 270.

FIG. 3 shows an application object 215. Each application object 215includes a set of common attributes used for system monitoring andalarms. For example, application objects 215 may include one or more of:a rate at which data is collected 310, a date of last update 320, a timeof last update 330, an error string for a data probe error message 340,an indication that the data probe was executed during the specifiedperiod 350, a one shot execution of data probe to set attribute values360, a signal to reinitialize a data probe 370, a description textstring to describe the application object 380, an alarm description tobe used in an alarm message 390, an object type 315, a log file tospecify the path of a log file used by a data probe 325, and anapplication object version 335. Application objects 215 serve as datafiles that temporarily store the data gathered by the data probes 270from the field devices 210. The remote collector 275 accesses andremoves the data in the application objects 215 and sends it to thehistorian 130 for long term storage.

Returning to FIG. 2, each workstation 250 may also be provided withnetwork and station resource monitoring software. The monitoringsoftware can include at least two application object interfaces: one tomonitor system and workstation resources, and a second to monitorworkstation and network resource errors. The application objectinterfaces can be run by a block processor 260 that can gather theresource data using control blocks (for which the block processor hasbeen programmed) as described in further detail below.

One or more host workstations 290 can be connected to serverworkstations 250 by communication network paths 230. The hostworkstations 290 can oversee the monitoring and data collection fromtheir associated workstations 250. The host workstation 290 mayconfigure the block processors 260 and collect the resource data (incontrol blocks) under supervision of the services portal 105 asdescribed below. In addition to the data probes 270, application objects215, and block processors 260, the host workstation 290 can include aremote collector 275, a block manager 285, and a block database 295.

The remote collector 275 collects application object data from one ormore workstations 250 in the form of control blocks 265. The remotecollector 275 receives process data from the communications network path230.

The block manager 285 configures each of the block processors 260, andapplication objects 215. The block manager 285 communicates with eachblock processor 260 using the communications network path 230. The blockmanager 285 specifies the desired control block types to be associatedwith the application objects 215. The block database 295 stores all ofthe block types that may be used to configure the block processors 260.The block database 295 is used for configuration and deploymentmanagement only. In one implementation, the block database 295 may beimplemented using an Informix database available from Foxboro. The blockmanager 285 accesses the block database 295 to provide the appropriateblock types to the block processors 260 of the workstations 250.

The services portal 105 can be connected to each host workstation 290 bycommunications network paths 230. The services portal 105 provides fordata collection and operates as a platform for the performance analysismonitor 100. The performance analysis monitor 100 includes a historian130, a performance web (PERFWEB) 255, and a block configurator 245. Thehistorian 130 supports the collection, storage, and retrieval of processdata and alarms. The historian 130 works in concert with a powerful setof client-server and web-enabled desktop tools that provide access tokey process management information (e.g., by the remote performancecenter 160 and through local onsite graphic user interfaces). Thehistorian 130 collects real-time process data from any process, system,device, and/or system resource.

The historian 130 recognizes and collects all types of process data fromapplication objects 215 and alarm objects that are obtained from theremote collector 275. The historian 130 also collects alarm and eventmessages including process alarms, operator actions, and system statusmessages and stores them in the historian database 130.

Installation and Deployment

Beginning with system initialization, the block configurator 245provides a graphical user interface 205 to control the block manager 285and block database 295 of the host workstations. The block configurator245 configures the block processors 260 for the performance analysismonitor 100 in conjunction with the block managers 285 and blockdatabase 295. The configurator 245 communicates with the block database295 using communications network paths 230. The graphical user interface205 may run on any platform, for example the graphical user interfacemay run on a PC-NT platform or other environment (e.g., Windows 2000 orXP).

The block configurator graphical user interface 205 includes an installfeature and a checkpoint feature. The install feature saves block typesto the block database 295 and generates application object files fromthe block types. The block manager 285 accesses the application objectfiles and transfers the application object files to each specific blockprocessor 260. Each block processor 260 then creates the applicationobject 215 from the application object files.

The block processor 260 of each workstation 250 creates the applicationobjects 215 directly from application objects files provided from theblock managers 285. The block processor 260 also initializes theapplication objects 215, defines the data probes 270 associated with theapplication objects 215, and performs periodic check pointing. Checkpointing may be used to obviate a global data probe execution after aworkstation reboot (which could overload the system).

The checkpoint feature updates the application objects' filecorresponding to the application object interface. An upload featurecorrects the block database 295 with the latest checkpoint update. Asave feature updates the block database 295, generates a map file,transfers the map file to the target block processor 260, recreates theapplication objects 215 on the target block processor 260 and, whereapplicable, reestablishes the updates from the block processor 260 andadjusts the checkpoint feature and upload features.

When a workstation 250 is rebooted, the context associated with localapplication object 215 is established by accessing a predetermined localapplication objects directory. For each application interface, the blockprocessor 260 opens the application interface's application objects fileand uses the information to create the application objects 215 and openthe application interface's initialization file and use the informationto initialize attributes to their check pointed values.

A detail display (with overlays) is provided for each block type. Detaildisplays for alarm blocks also are provided that include the viewing ofthe alarm state and the acknowledging of the alarm.

The structure will be:

CMP.r file containing a list of the Compound Names.

<COMPOUND>.r file containing a list of the Block Names in a specificCompound.

<BTYPE>.fdf Display File template for each specific block type.

<BTYPE_OVERLAY>.fdf Overlay Display File template for each specificblock type.

The .r files and the .fdf files are disseminated to each workstation250. When a compound or a block (instance) is added, the .r files areupdated in each workstation 250.

The performance analysis monitor 100 presents measurement and alarminformation concerning workstation performance using the applicationobject variables. Monitoring blocks are used to gather and update theapplication object variables from associated data probes. Alarms areused to warn the manufacturer of out of specification conditions atspecific field devices that may indicate imminent device failure, unsafeconditions, or unacceptable product.

Alarming may be configured using dedicated alarm blocks. For example,the following alarm block types may be provided: low, low low andrate-of-change on one measurement; high, high high and rate-of-change onone measurement; and state alarm on one measurement.

The alarm block may incorporate one or more alarm objects. The AlarmObjects may include alarm attributes. Examples of High Absolute Alarmsare:

<Application>:<Object>.HA00OP Alarm Option <Application>:<Object>.HA00GRAlarm group <Application>:<Object>.HA00PR Alarm Priority<Application>:<Object>.HA00LM Alarm Limit <Application>:<Object>.HA00DBAlarm Deadband <Application>:<Object>.HA00TX Alarm Text<Application>:<Object>.UNACK <Application>:<Object>.ALMSTA[<Application>:<Object>.PRTYPE] [<Application>:<Object>.CRIT]

The block processor 260 creates the applications and application objectsdirectly from map files, creates the applications and applicationobjects with alarm attributes; initialize applications; get values tosource application objects (e.g., instead of connection mapping) andperform periodic check pointing.

Performance Enhancement Business Model

The performance analysis monitor 100 provides a services supplier theopportunity to create and implement a new business model with theservice portal 105 serving as the supplied hardware. This business modelrecognizes the availability of cost savings to potential clients byusing the performance analysis monitor 100 to optimize clientutilization of capital assets to maximize return on investment (ROI) andprocess output. One example of this new business model has beendeveloped as a Performance Alliance Agreement.

FIG. 4 is a flowchart of the Performance Alliance Agreement businessmodel 400. Interest in an agreement is assessed 405 and the decision toproceed is made. The manufacturer may choose to have a proof of conceptdemonstration 410 performed prior to entering into a full agreement. Ifthe proof of concept path 415 is not chosen, the process continues withthe manufacturer and supplier assigning alliance managers 480. If theproof of concept path 415 is chosen, the proof of concept testing isgenerally performed on one or a few of the manufacturer's processeschosen jointly by the manufacturer and the supplier 420. The first stepis identifying needed improvements in the process 430, followed bydeveloping the baseline and choice of dynamic performance measures(DPMs) 440. The improvements are executed 450 using the system withcontinuous tuning of the system and the improvement is evaluated 460 bycomparison to the baseline 440. Assuming a successful demonstration 470,the manufacturer and supplier assign alliance managers 480, who enterinto a performance alliance agreement 490, whereby the established DPMsfrom step 440 are used to develop the baseline for each of themanufacturer's processes, needed improvements are identified 465,executed 475, and evaluated for the economic value added (EVA) 485. Theprocess is continuously evaluated and improved until it is no longereconomically a sound investment to implement additional improvements.

In a Performance Alliance Agreement between a manufacturer and asupplier these fundamentals are used to develop a mutually beneficialrelationship that pools the experience and intellectual capital of bothparties to achieve improved financial results by leveraging the deployedassets of the manufacturer. This is realized through:

1. The joint selection of areas in the manufacturing operations targetedfor improvement;

2. An analysis of the potential economic gain that may be realized foreach selected operation;

3. Agreement on the commercial terms for implementing each improvementactivity;

4. Identifying and implementing dynamic performance measures (DPM's);

5. The calculation of the baseline of economic performance for eachoperation by running the dynamic performance measures (invisible) for anagreed upon baseline period;

6. The execution of each of the improvement activities;

7. Determination of the economic value added through ongoing DPManalysis; and/or

8. DPM's are monitored on an ongoing basis to ensure that continuousimprovements are occurring.

Performance services are intended to ensure that the economic valuegenerated by such an alliance is greater than the cost of the services.

In order to enhance system performance, a review of business strategyand market conditions is performed to identify opportunities forperformance improvement that are consistent with the business strategy,the financial, the human resources, and the fundamentals of the businessrelationship, (including mutual expectations of risk management andcommensurate rewards for both parties).

The conclusion, if agreement is reached, is a commitment to proceed withan action plan that includes allocation of financial and human resourcesto execute the plan. If agreement is not concluded the parties have thechoice of continuing the Assess Interest discussion or adopting adifferent approach to performance improvement.

Entering into a performance alliance sometimes poses a challenge to thetraditional business model and adjustments may be required to thecultural business environment to accommodate a long-term benefit andrisk-sharing partnership. Significant to this adjustment is theacceptance of DPM as metrics of performance baseline and improvementsrealized that require reconciliation with the existing standard internalmanagement information system-derived performance reports. Developingthe cooperative model necessary to gain experience with solving theseand other operational issues can be accomplished in a proof of conceptperformance contract (path 415) between the supplier and themanufacturer for one or two sites or areas in order to build mutualtrust and confidence to accept this new approach to a businessrelationship that extends beyond the typical legal definitions of anagreement.

One goal is to determine how the business can be improved, by usingintegrated solutions that reduce opportunity cost, while supporting theneed for operational agility, with continuously current solutions. Toacquire the necessary funding, the migration plan may define howpotential changes will yield an acceptable ROI within a reasonablepayback period. The ability to support the vision, meet project ROI andpayback requirements, and improve the on-going Return on Assets (ROA) isthe a core function of an effective migration plan, and the value ofcompleting a Benefit Study and Business Case Analysis (described below).

The Benefit Study and Business Case Analysis should answer the followingquestions:

1. What is the business vision, and the operational strategy and goals?

2. What is the “As-Is” enterprise model? Enterprise models are pictorialrepresentations of the organization, its goals, workflow, productionprocess, and data flow. They can be easily produced and verified by theprocess owners. Thereafter, they help focus and improve the followingtypes of analysis.

3. What are the Key Process Inputs (KPIs) and Key Process Outputs (KPOs)for each step in the existing work process or production models? KPIsand KPOs may include: goals, schedules, information, labor, materials,equipment, and energy. How is quality managed with regard to each KPI orKPO? What are the activity based cost drivers? What is the capacity andthroughput? How are decisions regarding the use of resources made? Arethey consistent? What's the net contribution to ROA? What is thevariance? What factors govern success and add value at each step?

4. What types of failures occur? How often do they occur? Do they gounnoticed? How severe are they? What are the risk priorities?

5. What is the “opportunity cost” within the enterprise's workflow(i.e., the cost of failures, poor decisions regarding resource usage,and gaps in current capabilities)?

6. What capabilities and characteristics are needed to satisfy thevision, and to limit/eliminate existing opportunity cost? Which areessential?

7. What functional gaps exist between the As-Is enterprise model, andthe defined vision and goals (i.e., the wish list)?

8. What types of success measures can be employed to manage theeffectiveness of the process and to support a continuous improvementprogram?

9. What would a “To-Be” model look like? One that is based on standards,and limits the need for customization. How will it improve the successmeasures?

10. What are the best “fit for purpose” solution elements? What is theinstalled cost and schedule for implementing the To-Be model, and toachieve “operational readiness”?

11. How should the transition be prioritized with regard to needs, “fit”and “viability” factors? How can the Implementation Plan maximize thenet positive cash flow from each improvement? Are there “low hangingfruit”? That is, improvements that can be implemented quickly to helpfund the more costly investments?

12. What is the ROI and payback period? How sensitive is the pro-formaROI with regard to potential risks?

13. Can capital leasing improve the net present value of cash flow andthe program's ROI?

14. How can the transition be managed to limit risks?

15. What are the benefits of completing the transition using a win/winperformance-based contract?

General Methodology

The payback requirement discovery and design efforts need to bethoroughly coordinated, and provide open communications between keybusiness and operations management personnel of the manufacturer, andthe Supplier. The Benefit Study (described above) provides:

1. Reviewing business opportunities, vision and goals, and facilitiesoperating requirements;

2. Completing detailed “as-is” vs. “to be” enterprise models definingthe production and work process for the business functions;

3. Defining the Business and Production Models. Identifying optimizationopportunities;

4. Specifying the sensor to boardroom integration requirements;

5. Defining a balanced set of dynamic performance measures (DPM's) basedon key performance factors;

6. Mapping requirements to applications and identifying the best-fit,least cost solutions;

7. Finalizing the “To-Be” model for implementation and developing aproject implementation & management plan, including:

-   -   A. Solution scope definition & budgets;    -   B. Installation requirements;    -   C. A pro-forma ROI;    -   D. Guaranteed performance contracting measurements;    -   E. Implementation and management plan; and    -   F. Lifetime support & alliance partnership plan.

Following the on-site study a performance improvement team submits aproposal that defines the improvement benefits and from which theseimprovements will be derived. Included in this proposal are optionalfunding project(s) approaches. A selection of approaches is availableincluding either a capital budget as a traditional project, or operatingbudget using the positive cash flow generated from the improvement.

In a traditional project capital funds are approved by management andassigned to the performance improvement project through the normalapproval process.

Today more companies are choosing to partner with a third party in orderto conserve capital and improve the return on capital employed ratio.

By using a shared investment model, the amount of capital required islimited. The manufacturer providing the funding for only the directout-of-pocket costs facilitates this. A percentage of these costs ispayable at the start of the performance improvement project and thebalance as the costs are incurred. Once the system is started theimproved performance metrics will be immediately available and a trendcan be plotted and compared against the target expectations. This trendis monitored and analyzed by experts from the supplier. This reduces therisk and provides incentive to the alliance to develop a close workingrelationship to limit the negative cash flow excursion and reach thecross over to operating budget funding. At this point the supplierstarts the clock to receiving pre-agreed performance measurementintervals. At the conclusion of this term of contract payments theownership of the system is transferred to the manufacturer and 100% ofthe improvement benefits accrue to the manufacturer.

With a shared benefit model, the operating budget is used to provide thefunding with the cost payments being offset until the performanceimprovement positive cash flow starts once the system is commissioned. Afixed percentage of the performance improvement benefits and the term isagreed and stipulated in the contract. Ownership of the performanceanalysis monitor improvements remains with the supplier. At the end ofthe term, (that depends on the percentage and value) ownership may betransferred to the manufacturer for a token sum to be stipulated.

A project evaluator financial modeling tool is used to predict the keyperformance benefits, payment schedule, cash flows and ROI term usingthe information gained from the performance improvement study. The ROIterm to cross into generating positive cash flow is shown as well as theestimated maximum negative cash flow obligation as a capitalappropriation.

To establish the benefit improvement the present baseline performancemust first be established. A processing plant control apparatus providesreal-time indications of performance of plant operations with respect tocurrent state of process means.

Identification of these economic performance metrics is made by acertified performance analyst (usually working for the supplier) using astandard methodology to derive the measures. Plant-level performancemeasures provide a starting point for the analysis of a total plant DPMstructure. Plant-level performance measures must next be decomposed todetermine the correct measures of performance at the area, and/or unitlevel.

This decomposition is accomplished via subsequent “Vollmann Triangle”analyses down to the lowest operational level in the plant. A completeplant analysis of this type is referred to as Vollmann decomposition. Itis important that the decomposition analysis continue down to the lowestpoint in the structure for which an operations person has authority andresponsibility. Ultimately, this top-down analysis will identify andspecify the appropriate measures of performance for each individual atall levels in the manufacturing operation.

Once this decomposition has been accomplished, and the appropriatemeasures of performance have been identified for the plant and each areaand unit then the process measurement requirements necessary to directlymake, calculate, or infer the lowest level of performance measures mustbe identified. In some cases, additional process sensors may be neededto effectively model or calculate the appropriate performance measures.

The performance analyst should investigate other potential alternativeinput for a DPM model prior to requesting the addition of a new physicalsensor.

Effective implementation starts at the lowest level in the performancemeasurement hierarchy. DPM's are implemented by bringing the processmeasurement values into the control system and using the capability ofthe I/A Series control package to directly measure, calculate, or infereach of the DPM's for each operational area.

The value of each DPM should be set up to be recomputed on a time orevent basis relative to the natural time constant of the particularplant section. The target value of each DPM should reflect the currenteconomic and/or market conditions that drive the plant's manufacturingstrategy.

Once the DPM's in one of the lowest level areas are implemented, workshould proceed to incorporate the other operational areas in the plantat this same level. After first level DPM's are operational, the nexthigher level should be developed and so on right up to the highest levelfor the operation. Each node in the DPM hierarchy should correspond to amanagement point in the organizational hierarchy. In this way DPM's areconsistent with the DPM's directly below and above them in the hierarchyand manager measures will always be directly dependent on theperformance of his or her subordinates.

The DPM analyst submits a complete written report for plant managerapproval. This is to insure that the performance metrics are alignedwith the plant and corporate business strategy. Once this signature isreceived an engineer ensures that the DPM's are implemented and thebaseline performance measurements are collected and analyzed for apre-determined a period before the improvement project is completed.

A team is formed with representatives from the supplier and themanufacturer to implement the improvement strategy. In many cases wheresoftware is used to improve the process (modeling & optimization, looptuning etc.) the services portal 105 with the software and applicationengineering installed, is located at the manufacturing location. Thisservices portal 105 has the ability to connect to the legacy systemfieldbus and via a communications network path to a remote monitoringstation (e.g. remote monitoring station 160) of the supplier. Thisenables the implementation to be developed and tested off-line prior toinstallation without interfering with the legacy system operations.Remote monitoring begins immediately after the improvement is ready tostart. This enables supplier performance analysts to continuouslymonitor the performance improvement without site intervention. If aperformance alarm occurs the team can immediately analyze the problemand take corrective measures.

In the proof of concept stage 410-470 the objective is the developmentof mutual confidence between the two companies working together for thefirst time in a performance improvement alliance. A successful outcomeis the goal of both parties and mitigating risk is a high priority. Thejoint operating know-how, engineering knowledge and industry experienceis a powerful combination enhanced by powerful tools and technology tomitigate as much as possible the risk factors of cultural and operatingchanges.

The team begins the analysis of the performance real time improvementmetrics derived from the DPM's to make sure that the trend is on a pathto meet the expected performance improvement targets established in thecontract. Periodic site visits and continuous remote monitoring are usedto improve the performance and the team communication. Reactions tobusiness strategy due to market conditions, lost opportunities and theperformance of the virtual profit centers created by the DPM methodologyare closely scrutinized and adjustment made as required to theimprovement strategy and if necessary to the baseline metrics.

The proof of concept project performance contract will stipulate bymutual agreement, certain measurement points to conclude that the testresults met or did not meet mutual expectations. Typical performancemeasures include:

-   -   Increased throughput    -   Reduced energy consumption    -   Reduced waste    -   Reduced inventory cost

With the successful conclusion of the proof of concept phase the partiesmeet at the executive level to conclude the Performance AllianceAgreement that sets out the relationship of the partners and themeasurement criteria for a long term mutually rewarding relationship.Both partners are strongly encouraged to assign Executive AllianceManagers to oversee all aspects of the alliance and to be aligned withthe business strategy of the manufacturer to manage, drive and reportprogress of the alliance.

Both partners also agree to assign Executive Sponsors to the Alliance toprovide the appropriate level of executive support to the allianceactivities.

Each partner agrees to assign other resources to the Alliance team asrequested by the Executive Alliance Manager.

The same methodology is used at remaining sites. As more sites are addedthe Alliance Managers will develop a uniform corporate commercialagreement for all sites using an internal RFP process. This willaccelerate the speed of improvement deployment and reduce cost.

The Performance Alliance Agreement (PAA) defines the relationship,responsibilities, measures and mutual expectations of a long-termrelationship. A PAA is the embodiment of this relationship that is basedon trust, team sprit with a common goal to improve the competitiveposition of the manufacturer through a combination of operating andtechnical experience and modern tools and engineering knowledge.

Economic Value Added (EVA) is the ultimate measure of the PerformanceAlliance Agreement. EVA is defined as: After tax operating income−costof capital×(total assets−current liabilities). EVA measures the excessof a company's operating income over the cost of the capital involved.

Once an Automation Process Modeling exercises has been completed it isoften tempting to believe the task is done and to essentially go back tobusiness as usual. In the dynamic competitive environment created by theglobalization of the past ten years this would be a huge mistake. Acontinuous performance improvement process should be built right intothe automation planning activities. Every action that results inimprovement of the performance measures should be followed by a searchfor the next action that may help. In this way the economic performanceof the operations will continually improve and the automation systemtechnology will become the decision support system to help drive theimprovement. Also, whenever a major change takes place in the company'smarkets, a new strategic analysis might need to be executed. This mayresult in a revised competitive strategy and new performance measures.Without this type of continuous strategic analysis the operations withinthe company may be working to the wrong performance measure.

To offset the problem the supplier may offer a suite of LifetimePerformance Services. These services are designed to continuouslymonitor the DPM's to insure that the operating performance gains are notnegatively affected by factors such as loop tuning, asset modifications,operating strategy, current technology upgrades operator variations etc.

A number of implementations have been described. Nevertheless, it willbe understood that various modifications may be made. For example,advantageous results may be achieved when the steps of the disclosedtechniques are performed in a different order and/or when components ina disclosed system, architecture, device, or circuit are combined in adifferent manner and/or replaced or supplemented by other components.Accordingly, other implementations are within the scope of the followingclaims.

1. A method of improving a manufacturing client's business performancecomprising: determining a current baseline business performance for theclient including identifying targeted areas of improvement in themanufacturing area, each targeted area being associated with one or moreindustrial processes; analyzing a potential economic gain for eachtargeted area; identifying dynamic performance measures for eachtargeted area; monitoring industrial process parameters within thetarget areas, each industrial process parameter being associated with anindustrial process; developing baseline dynamic performance measures ofthe target areas based on the monitoring of the industrial processparameters; analyzing the baseline dynamic performance measures toidentify areas within the targeted areas of improvement foroptimization; optimizing industrial process parameters associated withthe identified areas within the targeted areas of improvement based onthe analysis of the baseline dynamic performance measures; andmeasuring, after the optimization, the industrial process parametersassociated with the identified areas and developing second baselinedynamic performance measures based on the measured industrial processparameters.
 2. The method of claim 1 wherein determining a currentbaseline business performance for the client includes on site study ofthe manufacturing area.
 3. The method of claim 1 wherein identifyingtargeted areas of improvement includes identification of deficientperformance of the process using economic analyses.
 4. The method ofclaim 3 wherein using economic analyses includes defining how potentialchanges will yield an increased return on investment over the determinedcurrent baseline business performance.
 5. The method of claim 1 whereinidentifying dynamic performance measures for each targeted area includesidentifying measurable process parameters that are directly related toeconomic performance of the targeted area.
 6. The method of claim 1wherein monitoring industrial process parameters within the target areasand developing baseline dynamic performance measures of the target areasincludes: observing multiple performances of the one or more processesassociated within each target area; and evaluating economic effects ofthe industrial process parameters.
 7. The method of claim 1 whereinmonitoring industrial process parameters includes establishing abaseline optimum value for each process parameter based on multipleperformances of each process.
 8. The method of claim 1 wherein analyzingthe baseline dynamic performance measures to identify areas within thetargeted areas of improvement for optimization includes evaluating theeconomic effects on a product of the industrial process parameters. 9.The method of claim 1 wherein determining a current baseline businessperformance for the client includes an on site study of a plant-levelprocess.
 10. The method of claim 1 wherein determining a currentbaseline business performance for the client includes analysis ofplant-level performance measures.
 11. The method of claim 10 furthercomprising decomposing the plant-level performance measures to a measureof performance at a manufacturing process level or a unit level.
 12. Themethod of claim 11 wherein the measure of performance is specific to themanufacturing process level or the unit level.
 13. The method of claim 1further comprising comparing the second baseline dynamic performancemeasures to the baseline dynamic performance measures to determinewhether the optimization resulted in an improvement.